Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation

A. Shintemirov, W. H. Tang, Z. Lu, Q. H. Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

The paper presents a simplified mathematical model of disctype transformer winding for frequency response analysis (FRA) based on traveling wave and multiconductor transmission line theories. The simplified model is applied to the FRA simulation of a transformer winding. In order to identify the distributed parameters of the model, an intelligent learning technique, rooted from particle swarm optimiser with passive congregation (PSOPC) is utilised. Simulations and discussions are presented to explore the proposed optimization approach.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages145-152
Number of pages8
Volume4448 LNCS
Publication statusPublished - 2007
Externally publishedYes
EventEvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG - Valencia, Spain
Duration: Apr 11 2007Apr 13 2007

Other

OtherEvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG
CountrySpain
CityValencia
Period4/11/074/13/07

Fingerprint

Transformer windings
Particle Swarm
Transformer
Parameter Identification
Frequency Response
Frequency response
Identification (control systems)
Theoretical Models
Learning
Transmission line theory
Transmission Line
Simulation Analysis
Modeling
Traveling Wave
Mathematical Model
Mathematical models
Optimization
Model
Simulation

Keywords

  • Particle swarm optimiser with passive congregation
  • Transformer winding mathematical model

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Shintemirov, A., Tang, W. H., Lu, Z., & Wu, Q. H. (2007). Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4448 LNCS, pp. 145-152)

Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. / Shintemirov, A.; Tang, W. H.; Lu, Z.; Wu, Q. H.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4448 LNCS 2007. p. 145-152.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shintemirov, A, Tang, WH, Lu, Z & Wu, QH 2007, Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4448 LNCS, pp. 145-152, EvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG, Valencia, Spain, 4/11/07.
Shintemirov A, Tang WH, Lu Z, Wu QH. Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4448 LNCS. 2007. p. 145-152
Shintemirov, A. ; Tang, W. H. ; Lu, Z. ; Wu, Q. H. / Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4448 LNCS 2007. pp. 145-152
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